fix depthwise conv tflite parser bug

mindspore/lite/tools/converter/parser/tflite/tflite_model_parser.cc

@@ -249,47 +249,52 @@ STATUS TfliteModelParser::ConvertGroupDepthwiseOp(schema::MetaGraphT* sub_graph)
           return RET_NULL_PTR;
         }
         auto data_shape = data_tensor->dims;
-        conv_attr->channelIn = data_shape[3];
-        conv_attr->channelOut = conv_attr->channelIn * attr->channelMultiplier;
-
-        // update attr
-        conv_attr->group = 0;
-        conv_attr->format = attr->format;
-        conv_attr->kernelH = attr->kernelH;
-        conv_attr->kernelW = attr->kernelW;
-        conv_attr->strideH = attr->strideH;
-        conv_attr->strideW = attr->strideW;
-        conv_attr->padMode = attr->padMode;
-        conv_attr->padUp = attr->padUp;
-        conv_attr->padDown = attr->padDown;
-        conv_attr->padLeft = attr->padLeft;
-        conv_attr->padRight = attr->padRight;
-        conv_attr->dilateH = attr->dilateH;
-        conv_attr->dilateW = attr->dilateW;
-        conv_attr->hasBias = attr->hasBias;
-        conv_attr->activationType = attr->activationType;
-
-        op->primitive->value.type = schema::PrimitiveType_Conv2D;
-        op->primitive->value.value = conv_attr.release();
-
-        // update weight
-        auto weight_id = op->inputIndex[1];
-        auto &weight_tensor = sub_graph->allTensors.at(weight_id);
-        if (weight_tensor->dataType == TypeId::kNumberTypeUInt8) {
-          auto status = TransFilterFormat<uint8_t>(weight_tensor.get(), kKHWC2CHWK);
-          if (status != RET_OK) {
-            MS_LOG(ERROR) << "Trans depthwiseConv Filter Format failed.";
-            return RET_ERROR;
-          }
-        }
-        if (weight_tensor->dataType == kNumberTypeFloat32 || weight_tensor->dataType == kNumberTypeFloat) {
-          auto status = TransFilterFormat<float>(weight_tensor.get(), kKHWC2CHWK);
-          if (status != RET_OK) {
-            MS_LOG(ERROR) << "Trans filter format failed.";
+
+        if (data_shape[3] == 1) {
+          conv_attr->channelIn = data_shape[3];
+          conv_attr->channelOut = conv_attr->channelIn * attr->channelMultiplier;
+
+          // update attr
+          conv_attr->group = 1;
+          conv_attr->format = attr->format;
+          conv_attr->kernelH = attr->kernelH;
+          conv_attr->kernelW = attr->kernelW;
+          conv_attr->strideH = attr->strideH;
+          conv_attr->strideW = attr->strideW;
+          conv_attr->padMode = attr->padMode;
+          conv_attr->padUp = attr->padUp;
+          conv_attr->padDown = attr->padDown;
+          conv_attr->padLeft = attr->padLeft;
+          conv_attr->padRight = attr->padRight;
+          conv_attr->dilateH = attr->dilateH;
+          conv_attr->dilateW = attr->dilateW;
+          conv_attr->hasBias = attr->hasBias;
+          conv_attr->activationType = attr->activationType;
+
+          op->primitive->value.type = schema::PrimitiveType_Conv2D;
+          op->primitive->value.value = conv_attr.release();
+
+          // update weight
+          auto weight_id = op->inputIndex[1];
+          auto &weight_tensor = sub_graph->allTensors.at(weight_id);
+          if (weight_tensor->dataType == TypeId::kNumberTypeUInt8) {
+            auto status = TransFilterFormat<uint8_t>(weight_tensor.get(), kKHWC2CHWK);
+            if (status != RET_OK) {
+              MS_LOG(ERROR) << "Trans depthwiseConv Filter Format failed.";
+              return RET_ERROR;
+            }
+          } else if (weight_tensor->dataType == kNumberTypeFloat32 || weight_tensor->dataType == kNumberTypeFloat) {
+            auto status = TransFilterFormat<float>(weight_tensor.get(), kKHWC2CHWK);
+            if (status != RET_OK) {
+              MS_LOG(ERROR) << "Trans filter format failed.";
+              return RET_ERROR;
+            }
+          } else {
+            MS_LOG(ERROR) << "The dataType of weight tensor is unsupported.";
             return RET_ERROR;
           }
+          weight_tensor->format = schema::Format_CHWK;
         }
-        weight_tensor->format = schema::Format_CHWK;
       }
     }
   }